Research And Implementation Of Network Quality Monitor Of Ios Platform Business

In recent years, with the rapid development of mobile Internet,mobile Internet field emerg out of a variety of new services, such as Micro blog, Micro message. Nowadays,more and more people use mobile Internet services to raise the efficiency of work and learning, and improve the quality of life and entertainment. With the increasing dependence on mobile Internet, peoplehas also been increasing demands on the service quality and user experience quality. In order to improve the quality of service to meet people ’s needs, it’s necessary to monitor the quality ofnetwork service.Firstly, this thesis briefly summarizesthe theoretical basis on the service quality monitoring of mobile Internet, including research status, scope and content, and related monitoring technology and other aspects. Secondly, it introduces the iOS platform architecture and its main development technologies. As the mobile Internet business installed on the mobile terminals as a general native application, this kind of business should be monitored by using passive monitoring mode. Relying on the End to End Network Monitor System developed by the laboratory center,and the study of operational principle of iOS platform, the thesis designs and implements a mobile Internet service quality monitor module on the iOS platform. In order to verify the performance of quality monitor module in the actual network environment, through analyzing the communication mechanism of mobile Internet social business, this thesis presents a group of QoE indicators for social services from the user’s experience perception perspective. Then,through combine QoS and QoE to analyzing, it summeds up the calculation method of the group of indicators. On this basis, the thesis analyzes the traffic of Micro blog, Micro message business, and extracted out the recognition characteristics of the applications and user behaviors. Afterwards, in the actual network environment,the thesis uses the monitor module to calculate the group of indicators. The results show that this set of indicators can better reflect the real user experience when using social applications.